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Global Stock Markets during Covid-19: Did Rationality Prevail?

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  • Talebi, Alireza
  • Bragues, George
  • Hadlul, Seham
  • Sharma, Agam

Abstract

This study assesses the validity of the Efficient Markets Hypothesis (EMH) during the Covid-19 period by evaluating whether various stock markets around the world accurately predicted economic performance in their respective countries. The underlying premise is that stock prices should discount future company cash flows, and the projection of these cash flows can be proxied by investors' ability to forecast macroeconomic conditions. We assess stock market performance from January 2020 to February 2022 in 16 countries, equally split between developed and emerging markets. While results varied, the study suggests that stock markets generally predicted economic activity during Covid-19. The modeling test indicated that stock markets significantly predicted economic activity in 11 out of 16 countries, particularly in developed markets. Furthermore, incorporating the stock market as a variable, improved economic forecasts in all 16 countries. Unlike other studies that mainly focused on the characteristics of share price movements, this research judges the rationality of stock markets against an external criterion. Ultimately, it suggests that EMH was mostly vindicated during the Covid-19 period.

Suggested Citation

  • Talebi, Alireza & Bragues, George & Hadlul, Seham & Sharma, Agam, 2025. "Global Stock Markets during Covid-19: Did Rationality Prevail?," Research in International Business and Finance, Elsevier, vol. 73(PA).
    • Handle: RePEc:eee:riibaf:v:73:y:2025:i:pa:s0275531924004033
    DOI: 10.1016/j.ribaf.2024.102610
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    as
    1. Samuel Tabot Enow, 2021. "The Impact of Covid-19 on Market Efficiency: A Comparative Market Analysis," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 9(4), pages 235-244.
    2. Jay Choi, Jongmoo & Hauser, Shmuel & Kopecky, Kenneth J., 1999. "Does the stock market predict real activity? Time series evidence from the G-7 countries," Journal of Banking & Finance, Elsevier, vol. 23(12), pages 1771-1792, December.
    3. Gili Yen & Cheng-few Lee, 2008. "Efficient Market Hypothesis (EMH): Past, Present and Future," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 11(02), pages 305-329.
    4. Mauro, Paolo, 2003. "Stock returns and output growth in emerging and advanced economies," Journal of Development Economics, Elsevier, vol. 71(1), pages 129-153, June.
    5. Fernandes, Leonardo H.S. & de Araujo, Fernando H.A. & Tabak, Benjamin M., 2021. "Insights from the (in)efficiency of Chinese sectoral indices during COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 578(C).
    6. Fama, Eugene F, 1981. "Stock Returns, Real Activity, Inflation, and Money," American Economic Review, American Economic Association, vol. 71(4), pages 545-565, September.
    7. Shiller, Robert J, 1981. "Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?," American Economic Review, American Economic Association, vol. 71(3), pages 421-436, June.
    8. Min Liu & Wei-Chong Choo & Chien-Chiang Lee, 2020. "The Response of the Stock Market to the Announcement of Global Pandemic," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(15), pages 3562-3577, December.
    9. Pedro Antonio González & José Luis Gallizo, 2021. "Impact of COVID-19 on the Stock Market by Industrial Sector in Chile: An Adverse Overreaction," JRFM, MDPI, vol. 14(11), pages 1-24, November.
    10. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    11. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    12. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    13. Dias Rui & Pereira João M. & Carvalho Luísa Cagica, 2022. "Are African Stock Markets Efficient? A Comparative Analysis Between Six African Markets, the UK, Japan and the USA in the Period of the Pandemic," Naše gospodarstvo/Our economy, Sciendo, vol. 68(1), pages 35-51, March.
    14. repec:pri:cepsud:91malkiel is not listed on IDEAS
    15. Fama, Eugene F, 1990. "Stock Returns, Expected Returns, and Real Activity," Journal of Finance, American Finance Association, vol. 45(4), pages 1089-1108, September.
    16. Geoffrey H. Moore, 1983. "Security Markets and Business Cycles," NBER Chapters, in: Business Cycles, Inflation, and Forecasting, 2nd edition, pages 139-160, National Bureau of Economic Research, Inc.
    17. Kuosmanen, Petri & Vataja, Juuso, 2019. "Time-varying predictive content of financial variables in forecasting GDP growth in the G-7 countries," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 211-222.
    18. Chatelais, Nicolas & Stalla-Bourdillon, Arthur & Chinn, Menzie D., 2023. "Forecasting real activity using cross-sectoral stock market information," Journal of International Money and Finance, Elsevier, vol. 131(C).
    19. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    20. Robert J. Shiller, 2015. "Irrational Exuberance," Economics Books, Princeton University Press, edition 3, number 10421.
    21. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November.
    22. Ólan T. Henry & Nilss Olekalns & Jonathan Thong, 2004. "Do stock market returns predict changes to output? Evidence from a nonlinear panel data model," Empirical Economics, Springer, vol. 29(3), pages 527-540, September.
    23. Evangelos Vasileiou, 2021. "Behavioral finance and market efficiency in the time of the COVID-19 pandemic: does fear drive the market?," International Review of Applied Economics, Taylor & Francis Journals, vol. 35(2), pages 224-241, March.
    24. Barro, Robert J, 1990. "The Stock Market and Investment," The Review of Financial Studies, Society for Financial Studies, vol. 3(1), pages 115-131.
    25. Samuel Tabot Enow, 2022. "Overreaction And Underreaction During The Covid-19 Pandemic In The South African Stock Market And Its Implications," Eurasian Journal of Business and Management, Eurasian Publications, vol. 10(1), pages 19-26.
    26. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 59-82, Winter.
    27. Rui Dias & Nuno Teixeira & Veronika Machova & Pedro Pardal & Jakub Horak & Marek Vochozka, 2020. "Random walks and market efficiency tests: evidence on US, Chinese and European capital markets within the context of the global Covid-19 pandemic," Oeconomia Copernicana, Institute of Economic Research, vol. 11(4), pages 585-608, December.
    28. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    29. Frezza, Massimiliano & Bianchi, Sergio & Pianese, Augusto, 2021. "Fractal analysis of market (in)efficiency during the COVID-19," Finance Research Letters, Elsevier, vol. 38(C).
    30. Tihana Škrinjarić, 2021. "Profiting on the Stock Market in Pandemic Times: Study of COVID-19 Effects on CESEE Stock Markets," Mathematics, MDPI, vol. 9(17), pages 1-20, August.
    31. Rosy Dhall & Bhanwar Singh, 2020. "The COVID-19 Pandemic and Herding Behaviour: Evidence from India’s Stock Market," Millennial Asia, , vol. 11(3), pages 366-390, December.
    32. Vincent Fromentin, 2022. "Time-varying causality between stock prices and macroeconomic fundamentals: Connection or disconnection?," Post-Print hal-04206765, HAL.
    33. Anthony Aylward & Jack Glen, 2000. "Some international evidence on stock prices as leading indicators of economic activity," Applied Financial Economics, Taylor & Francis Journals, vol. 10(1), pages 1-14.
    34. Fromentin, Vincent, 2022. "Time-varying causality between stock prices and macroeconomic fundamentals: Connection or disconnection?," Finance Research Letters, Elsevier, vol. 49(C).
    35. Dragomirescu-Gaina, Catalin & Philippas, Dionisis, 2022. "Local versus global factors weighing on stock market returns during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 46(PA).
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    More about this item

    Keywords

    Efficient Market Hypothesis (EMH); OECD countries; Covid-19; Economic Tracker;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G1 - Financial Economics - - General Financial Markets
    • G40 - Financial Economics - - Behavioral Finance - - - General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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